Abstract: Due to the complex model of cables, non-linearity, and uncertainties that exist in Cable-Driven Parallel Robots (CDPRs), this paper proposes a bio-inspired intelligent approach to overcome these challenges. This method, Brain Emotional Learning (BEL), mimics the emotional aspect of the mammal brain. Because of its easy-to-implement mathematical model, the Brain Emotional Learning-Based Intelligent Controller (BELBIC) brings fast adaptation, robustness, and low computational cost. The core idea of this paper is to define new saturated learning functions that eliminate the necessity of calculating the Jacobian matrix and forward kinematics in the control loop while still ensuring positive tensions. To evaluate the effectiveness of the proposed method, an experimental study was conducted using a plotter CDPR. The experimental results indicate that BELBIC can be adopted as a new approach in the trajectory tracking problem in the context of CDPRs, as it provides an acceptable tracking error (less than 10 degrees) without using the Jacobian matrix in the feedback loop.

Abstract: Uncertainties in the kinematic and dynamic parameters of a parallel robot are unavoidable. The problem is more crucial in the cases where the manipulator interacts with the environment and when it is large–scale or deployable. Furthermore, precise measurement of the velocity of the end-effector is almost inaccessible in practice. This paper addresses the above shortcomings by designing an adaptive trajectory tracking controller with merely position feedback of joint and task space variables. The simplicity of implementation, separation of adaptation laws of dynamic and kinematic parameters, and reduction of the number of adaptation laws such that in some cases, e.g., cable-driven robots, it is identically equivalent to the number of unknown parameters are some advantages of the proposed controller. The method’s efficiency is shown via implementation on a cable-driven parallel manipulator and an intraocular surgery robot.

Abstract: This paper presents a model-free robust nonlinear PD (R-NPD) controller for cable-driven parallel manipulators (CDPMs) in joint space. Generally, in various mechanical manipulators and in particular CDPMs for fast and high-precision tracking, a precise dynamic model is required. However, the dynamic model of the robot is always contaminated with uncertainties such as nonlinear and time-varying parameters as well as external disturbances. For this purpose, in the proposed controller structure, the time-delay estimation (TDE) technique is used to indirectly use the robot dynamics into the control structure without need of its prior knowledge. Furthermore, a nonlinear PD controller is designed in joint space in such a way that the robot can track the reference trajectory quite fast and accurate, without the need for any auxiliary sensors. The stability of the closed-loop system has been examined through Lyapunov direct method, and it has been shown that tracking error remains uniformly ultimately bounded. Finally, to demonstrate the effectiveness of the proposed controller, simulations and experiments have been performed on two different categories of CDPMs, whose results show that the proposed control scheme outperforms modified TDE control method in practice.

Abstract: Background and Objectives: Fast-tracking of reference trajectory and performance improvement in the presence of dynamic and kinematic uncertainties is of paramount importance in all robotic applications. This matter is even more important in the case of cable-driven parallel robots due to the flexibility of the cables. Furthermore, cables are limited in the sense that they can only apply tensile forces, for this reason, feedback control of such robots becomes more challenging than conventional parallel robots. Methods: To address these requirements for a suspended cable-driven parallel robot, in this paper a novel adaptive fast terminal sliding mode controller is proposed and then the stability of the closed-loop system is proven. In the proposed controller, a nonlinear term as a fractional power term is used to guarantee the convergent response at a finite time. Results: At last, to show the effectiveness of the proposed controller in tracking the reference trajectory, simulations and the required experimental implementation is performed on a suspended cable-driven robot. This robot, named ARAS-CAM, has three degrees of transmission freedom. Conclusion: The obtained experimental results confirm the suitable performance of this method for cable robots in the presence of dynamic uncertainties.

Abstract: Despite model-based approaches are capable of providing acceptable performance, but they require complex dynamics modeling, which make them difficult to apply. To overcome this problem, a time-delay learning-based controller as a model-free approach is proposed for fully-constrained cabledriven parallel robots (CDPRs) considering the positive cable force constraints and actuator limitations. The proposed method uses the memory of control effort as a learning element to linearize the system. In addition, using a saturation function in control law has provided the opportunity to ensure all the cables are bounded and remain in tension, to guarantee both the positive cable forces and actuator limitation. Moreover, in the proposed method, we are able to eliminate the requirement of measurement of the task variables, which is very costly by using expensive external positioning measurement systems. Finally, a fully-constrained CDPR is used to test the proposed method, and the results demonstrate how effective is the method in terms of tracking performance as a model-free controller.

Abstract: Concerning the lack of knowledge about nonlinearity and uncertainties existing in the cable-driven robot models, an intelligent controller is proposed in this paper to overcome the lack of knowledge. Brain Emotional Learning is one of the bio-inspired algorithms which mimics the emotional part of the mammals’ brain. Not only does the Brain Emotional Learning Based Intelligent Controller (BELBIC) enable us to reach quick adaptation and robustness, but the computations are also very efficient. By defining the BELBIC learning functions with saturation functions, it is shown that the need to calculate the Jacobian matrix and forward kinematics in the feedback loop is eliminated, while guaranteeing positive tensions to the robot. The performance of the proposed method is examined by experiments, and results show that BELBIC can perform well in terms of tracking error.

Abstract: In this paper, a new type of planar cable-driven parallel robot with parallelogram links is investigated. In such a design, the cables pass through multiple pulleys in order to make parallelogram links, instead of directly connecting to the moving platform. By using such configurations, one can greatly improve the robot's kinematic performance without adding the cost of extra actuators. In this paper, a multi-objective optimization method is presented for this type of cable-driven robot using various kinematic indices. To this end, two planar robot configurations with parallelogram links are first introduced and the kinematic formulations are presented. Then, based on well-known kinematic indices like the size of the wrench closure workspace, the dexterity, and the natural frequency, the optimal Pareto front of the design parameters is obtained. Finally, the above procedure is applied to the design of a planar cable-driven parallel robot and the optimal design is presented.

Abstract: Employing redundant cables to control the moving platform of cable-driven parallel robots (CDPRs) not only ensures that the cables are in tension during the robot maneuvers, but can also significantly improve the kinematic performance indices of the robot. This paper presents a new structure for planar CDPRs that use parallelogram links instead of conventional links, to preserve both of these characteristics. Exploiting parallelogram links eliminates the necessity to use additional actuators in the design of planar CDPRs, while redundancy of cables is still preserved in the robot structure. The main innovation of the paper is to provide a general formulation for the proposed structure that covers all possible designs for planar CDPRs, such that the most suitable design is adopted for the demanded application. The proposed structure is applied to two cases of planar CDPRs, namely fully constrained and redundantly actuated, while the simulation results verifies the effectiveness of the proposed analysis.

Abstract: Increasing the speed and precision of operation in cable robots is crucial due to the flexibility of cables. On the other hand, due to the frequent dynamical uncertainties present in cable robots, providing a robust control method is necessary. The performance of the fast terminal sliding mode (FTSM) controller has been investigated in various systems, which ensures that the state of the system is rapidly converged to the equilibrium point at a finite time. In this paper, the FTSM controller has been developed in such a way to be able to track the optimal robot path in the presence of dynamic uncertainties at different operating speeds. The main innovation of this paper is to provide an adaptive robust control method for controlling cable robots and analyzing the stability of the closedloop control system based on the Lyapunov stability theory. In order to demonstrate the effectiveness of the proposed controller, simulation results, as well as experimental implementation on ARAS–CAM, a four cable suspended robot with three degrees of freedom, has been investigated and it is shown that the proposed controller can provide suitable tracking performance in practice.

Description: The aim of this invention is to present an easy-to-install painting robot that is manufactured at minimal cost. The main distinction of this invention compared to other painting robots lies in its integrated electronic structure, which makes reinstallation of the robot arm simple. In other words, although the robot spans several meters in size, all its mechanical and electronic components are compactly housed within a small electronic box only a few centimeters wide, providing a unified structure for its main parts. Additionally, the straightforward mechanical design used in this robot significantly reduces manufacturing costs compared to other painting robots. Using a cable and belt mechanism instead of rigid links not only creates a much larger workspace for the robot but also greatly simplifies its calibration, making it more user-friendly. This invention enables the artist's digital artwork to be executed on the painting canvas through virtual interfaces. Furthermore, by incorporating electronic user interfaces, there is no longer a need for personal computers to adjust the robot settings. This not only simplifies the robot's usability but also drastically reduces its operational cost, making it a budget-friendly option for recreational settings.